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AI: What it is, and should you use it AI: What it is, and should you use it In this E-Guide: The hype surrounding artificial intelligence (AI) and all its potential applications is seemingly unending—but, could it really as powerful as people say it is? AI (artificial intelligence) Keep reading to discover what AI is by definition, why it’s becoming a hot commodity for contact centers, and the pros and cons of implementing it for yourself. 5 trends driving AI in contact centers The pros and cons of customer service AI Page 1 of 21 SPONSORED BY AI: What it is, and should you use it AI (artificial intelligence) Margaret Rouse, WhatIs.com Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of AI (artificial information and rules for using the information), reasoning (using rules to reach approximate intelligence) or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision. 5 trends driving AI in contact centers AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as The pros and cons of Apple's Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is customer service AI an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention. Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services. While AI tools present a range of new functionality for businesses ,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given Page 2 of 21 SPONSORED BY AI: What it is, and should you use it in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely. Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in AI (artificial general. Researchers and marketers hope the label augmented intelligence, which has a intelligence) more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them. 5 trends driving AI in contact centers The pros and cons of customer service AI Page 3 of 21 SPONSORED BY AI: What it is, and should you use it The linked image cannot be displayed. The file may have been moved, renamed, or deleted. Verify that the link points to the correct file and location. AI (artificial intelligence) 5 trends driving AI in contact centers The pros and cons of customer service AI Types of artificial intelligence Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI Page 4 of 21 SPONSORED BY AI: What it is, and should you use it systems that exist today to sentient systems, which do not yet exist. His categories are as follows: • Type 1: Reactive machines. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to AI (artificial inform future ones. It analyzes possible moves -- its own and its opponent -- and intelligence) chooses the most strategic move. Deep Blue and Google's AlphaGO were designed for narrow purposes and cannot easily be applied to another situation. 5 trends driving AI in • Type 2: Limited memory. These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are contact centers designed this way. Observations inform actions happening in the not-so-distant future, such as a car changing lanes. These observations are not stored permanently. The pros and cons of • Type 3: Theory of mind. This psychology term refers to the understanding that customer service AI others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist. • Type 4: Self-awareness. In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist . Page 5 of 21 SPONSORED BY AI: What it is, and should you use it The linked image cannot be displayed. The file may have been moved, renamed, or deleted. Verify that the link points to the correct file and location. AI (artificial intelligence) 5 trends driving AI in contact centers The pros and cons of customer service AI Page 6 of 21 SPONSORED BY AI: What it is, and should you use it Examples of AI technology AI is incorporated into a variety of different types of technology. Here are seven examples. • Automation: What makes a system or process function automatically. For example, robotic process automation (RPA) can be programmed to perform high-volume, AI (artificial repeatable tasks that humans normally performed. RPA is different from IT intelligence) automation in that it can adapt to changing circumstances. • Machine learning: The science of getting a computer to act without programming . 5 trends driving AI in Deep learning is a subset of machine learning that, in very simple terms, can be contact centers thought of as the automation of predictive analytics. There are three types of machine learning algorithms: The pros and cons of o Supervised learning: Data sets are labeled so that patterns can be detected and used to label new data sets customer service AI o Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or differences o Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback • Machine vision: The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision. • Natural language processing (NLP): The processing of human -- and not computer -- language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and Page 7 of 21 SPONSORED BY AI: What it is, and should you use it decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition. • Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. Researchers are also using machine learning to build AI (artificial robots that can interact in social settings. • Self-driving cars: These use a combination of computer vision, image recognition intelligence) and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians. 5 trends driving AI in contact centers AI applications The pros and cons of Artificial intelligence has made its way into a number of areas. Here are six examples. customer service AI • AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aid patients through the billing process, and virtual health assistants that provide basic medical feedback. • AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide Page 8 of 21 SPONSORED BY AI: What it is, and should you use it immediate service to customers. Automation of job positions has also become a talking point among academics and IT analysts.
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